Evaluating the potential for measuring river discharge from space

被引:262
作者
Bjerklie, DM
Dingman, SL
Vorosmarty, CJ
Bolster, CH
Congalton, RG
机构
[1] Univ New Hampshire, Dept Earth Sci, Durham, NH 03824 USA
[2] Univ New Hampshire, Inst Study Earth Oceans & Space, Durham, NH 03824 USA
[3] Univ New Hampshire, Dept Nat Resources, Durham, NH 03824 USA
基金
美国国家航空航天局;
关键词
estimation of river discharge; satellite monitoring of rivers; river channel hydraulics; multiple regression analysis of river hydraulic data; multi-variate river discharge ratings; WATER-LEVEL CHANGES; AMAZON RIVER; INUNDATION AREA; FLOOD; CHANNEL; MODEL;
D O I
10.1016/S0022-1694(03)00129-X
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Numerous studies have demonstrated the potential usefulness of river hydraulic data obtained from satellites in developing general approaches to tracking floods and changes in river discharge from space. Few studies, however, have attempted to estimate the magnitude of discharge in rivers entirely from remotely obtained information. The present study uses multiple-regression analyses of hydraulic data from more than 1000 discharge measurements, ranging in magnitude from over 200,000 to less than 1 m(3)/s, to develop multi-variate river discharge estimating equations that use various combinations of potentially observable variables to estimate river discharge. Uncertainty analysis indicates that existing satellite-based sensors can measure water-surface width (or surface area), water-surface elevation, and potentially the surface velocity of rivers with accuracies sufficient to provide estimates of discharge with average uncertainty of less than 20%. Development and validation of multi-variate rating equations that are applicable to the full range of rivers that can be observed from satellite sensors, development of techniques to accurately estimate the average depth in rivers from stage measurements, and development of techniques to accurately estimate the average velocity in rivers from surface-velocity measurements will be key to successful prediction of discharge from satellite observations. (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:17 / 38
页数:22
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